Open AccessImplementation of Image Resampling Algorithm Based on Compressed Sensing
Author(s) -
Denghui Li,
Yanhong Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1732/1/012071
Subject(s) - resampling , compressed sensing , computer science , signal (programming language) , sampling (signal processing) , distortion (music) , algorithm , signal reconstruction , block (permutation group theory) , image (mathematics) , iterative reconstruction , signal processing , computer vision , artificial intelligence , mathematics , telecommunications , bandwidth (computing) , filter (signal processing) , amplifier , radar , geometry , programming language
In this paper, the sampling rate of traditional signal reconstruction should be more than 2 times the maximum frequency of the original signal in order to ensure the non-distortion reconstruction of the signal. The theoretical knowledge of compressed sensing is deeply analysed, and the image signal is reconstructed by block compression sensing method. Experiments show that the sampling rate is more higher, and the reconstruction error is more smaller, but the processing complexity is more higher; conversely, the lower the sampling rate, the lower the processing complexity, the greater the reconstruction error.